{"id":"W4312547917","doi":"10.1016/j.procs.2022.09.216","title":"Deep Learning based Currency Exchange Volatility Classifier for Best Trading Time Recommendation","year":2022,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Currency; Deep learning; Volatility (finance); Artificial neural network; Artificial intelligence; Stochastic volatility; Machine learning; Foreign exchange market; Econometrics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005745296,0.0004206358,0.0008329957,0.0009584182,0.0002856857,0.0008743139,0.0009086451,0.0007640502,0.002291883],"category_scores_gemma":[0.001163888,0.0002321439,0.0004645231,0.0008154172,0.0001042812,0.0008134542,0.0003819828,0.001043992,0.0008838637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000580199,"about_ca_system_score_gemma":0.0006926974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007979683,"about_ca_topic_score_gemma":0.01026071,"domain_scores_codex":[0.9997003,0.00003818774,0.00003368961,0.00006494108,0.0001027722,0.00006017782],"domain_scores_gemma":[0.9996525,0.000103592,0.00002911527,0.00003364976,0.000155528,0.00002567128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004968931,0.0007362326,0.01105452,0.00008638001,0.0001708246,0.000165803,0.00005336782,0.1544923,0.00972075,0.002622406,0.009089993,0.8113105],"study_design_scores_gemma":[0.00001289844,0.00004833467,0.0009191143,0.000007748466,0.00001532351,0.00002958073,0.00001003692,0.9953961,0.00227383,0.000606579,0.0006732491,0.000007240951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3411083,0.002698723,0.6394057,0.001086524,0.0004408483,0.0001661824,0.00128422,0.003345388,0.01046416],"genre_scores_gemma":[0.8865303,0.0006818289,0.1011896,0.0002414297,0.0001274393,0.0000785847,0.001579837,0.00004132972,0.009529634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007979683,"threshold_uncertainty_score":0.01586646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1574407578264843,"score_gpt":0.3972791700956516,"score_spread":0.2398384122691673,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}